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LLM Orchestration

LLM orchestration without the infrastructure

Building multi-model workflows means managing four API integrations, normalizing response formats, and writing synthesis logic. Synero runs all of it behind a single endpoint.

Free account: 3 full queries, no card. Then pay as you go from $5 of credit, no subscription.

POST/api/query

Synero handles parallel execution, streaming, synthesis, and agreement analysis. You send one request and get back structured multi-model output.

Your app

POST /api/query

Synero

Asks in parallel

GPTClaudeGeminiGrok

Combined answer

Plus where they agree

Capabilities

01Parallel Execution

Up to four models execute simultaneously with independent streaming. Total latency is the slowest model, not the sum of all models.

02Synthesis and Agreement Score

A dedicated synthesis step reads every response and writes one answer, and an agreement analysis returns a 0-100 score. No prompt engineering required.

03Model Routing

Pick up to four of the 20 models with the models array (one per provider) or a preset (solo, duel, council, deep, or auto to let Synero pick per question). The legacy config object and council tiers still work.

04Normalized Responses

Every model returns data in the same structure regardless of provider. No more parsing four different API response schemas.

05Error Isolation

If one model fails or returns nothing, the others still return results, and the failure is reported as an advisor-error event.

06Council Templates

Pass a template slug such as code-review, due-diligence, or deep-research to turn the advisors into domain specialists with one parameter.

Code Example

// Use a template to switch between configurations
const response = await fetch('https://synero.ai/api/query', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    prompt: 'Evaluate the risk of migrating from REST to GraphQL',
    template: 'architecture-decision', // pre-configured advisor roles
  }),
});

// Response includes:
// - Advisor responses (streamed via SSE)
// - Synthesis combining all perspectives
// - A consensus event with the agreement score
// - Metadata: models used, token counts, latency per advisor

Frequently asked questions

Why not build my own orchestration layer?

You can, but it means maintaining four provider integrations, handling rate limits and retries for each, normalizing response formats, building synthesis logic, and managing credential rotation. Synero handles all of this, letting you focus on your application logic.

Can I use only specific models?

Yes. Send models (1 to 4 model ids, one per provider) or a preset (solo, duel, council, deep, or auto to let Synero pick per question). Use a single model for simple questions and the full council for important decisions. Any of the 20 available models can be picked.

Does orchestration add latency?

Models run in parallel, so total latency is set by the slowest model, not the sum. The synthesis step adds time after the answers finish. Pass synthesis: false to skip it and get only the advisor answers.

How do I handle errors gracefully?

If a model fails or returns no text, you receive an advisor-error event for that advisor while the others keep streaming. If every advisor fails, you get a fatal error event.

Skip the orchestration work

Parallel models, synthesis, and an agreement score from one endpoint. Free to try, no card.

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